Human languages are rich and complicated, including huge vocabularies with complex grammar and contextual meaning. Machine interpretation of human language, even in a very limited way, is an extremely complex task and continues to be the subject of extensive research. Providing users with the ability to communicate their desires to an automated system without requiring users to learn a machine specific language or grammar would decrease learning costs and greatly improve system usability. However, users become quickly frustrated when automated systems and machines are unable to interpret user input correctly, resulting in unexpected results.
Natural language input can be useful for a wide variety of applications, including virtually every software application with which humans are intended to interact. Typically, during natural language processing the natural language input is separated into tokens and mapped to one or more actions provided by the software application. Each application can have a unique set of actions. Consequently, it can be both time-consuming and repetitive for software developers to draft code to interpret natural language input and map the input to the appropriate action for each application.
The Internet in particular has provided users with a mechanism for obtaining information regarding any suitable subject matter. For example, various web sites are dedicated to posting text, images, and video relating to world, national, and/or local news. A user with knowledge of a Uniform Resource Locator (URL) associated with one of such web sites can simply enter the URL into a web browser to be provided with the web site and access content thereon. Another conventional manner of locating desired information from the Internet is through utilization of a search engine. For instance, a user can enter a word or series of words into a search field and thereafter initiate the search engine (e.g., through depression of a button, one or more keystrokes, voice commands, . . . ). The search engine then utilizes search algorithms to locate web sites related to the word or series of words entered by the user into the search field, and the user can then select one of the web sites returned by the search engine to review content therein.
As more and more people have begun to utilize the Internet, it has become apparent that revenue opportunities exist for small and large businesses alike. For instance, many retail companies utilize the Internet to sell goods online, thereby reducing costs associated with managing and maintaining a store location, providing an ability to centralize inventory, and various other similar benefits that result in decreased costs that are passed on to customers. Given this increased use of the Internet for generating business and/or revenue, it has also become apparent that the Internet can be utilized as an advertising mechanism. In one example, an individual who enters the key word “flower” into a search engine may be interested in purchasing flowers—thus, it is beneficial for a company that sells flowers to advertise to that user at the point in time that the user is searching for the aforementioned term. Oftentimes users will see the advertisements and click on such advertisements to purchase flowers, thereby creating business for the flower retailer. Furthermore, the search engine is provided with additional revenue by selling advertisement space for a particular period of time to the flower retailer when the term “flower” is utilized as a search term. In a similar example, a sporting goods company may wish to display advertisements on a web site related to sports, and can purchase advertising space for a limited amount of time on the web site. Again, the buying and selling of advertising space can lead to increased revenue for an owner of the web site as well as the advertiser.